Users spend an immense amount of time interacting with content on social media websites. On one popular social media website, for example, over a billion active users spend a total of over ten million hours each month interacting with the website. These users can often produce hundreds of millions of content posts each day. When users access such websites, the social media web site can select content such as other users' posts, news feeds, event notifications, and advertisements to display to the users. Selecting content items that users are likely to find helpful or relevant increases the chances that users will interact with those content items and that they will return to the website in the future.
Over time, topics and actions discussed on social media fall into and out of favor. Topics or actions that are currently being performed or discussed are referred to as “trending.” Determining trending topics and actions can be extremely valuable in selecting content items or in convincing advertisers to utilize social media channels to reach potential customers. For example, trending topics and actions can be helpful to inform marketing decisions, to provide recommendations for other users, to predict resource usage, to draw analogies to other similar topics and actions, etc. However, classifying a topic or action as trending can be difficult. For example, trends that may exist for a segment of social media contributors, such as those who share a particular geographical location, may not be readily apparent from an analysis of general social media posts. Furthermore, performing an in-depth analysis on combinations of the millions of social media posts that are created every hour can become computationally intractable.